Use Digital Twins to Contextualize Data

refer to the following how to guide for leveraging digital twins for energy monitoring user scenario digital twins will model the asset as an energy monitoring machine located at several plant sites the instances for the model will be the specific energy monitoring machines at each site the power generated will be used to generate values for cost, energy used, and energy rate the timestamp value will be used to generate values for the attributes of season, start hour, and energy rate description values for power generated will be sent through the topic devicehub alias p2 electrical panel l3 machine2 timestamp values from one of the energy monitoring machines will be sent through the topic flowtodt emd l3 machine2 sample output payload from instance this user scenario will be based on the following sample output payload from one instance { "time" "2023 04 13t17 00 00 000z", "plant" "toronto", "line" "line 1", "asset" "machine 2", "shift" 2, "energyused" 2 51, "energyrate" 15 1, "energyratedescription" "on peak", "season" "winter", "cost" 37 9, "timestamp" 1681408544466, "starthour" "2023 04 13t17 00 00 000z" } step 1 create digital twins model you will first need to create the model that will store the instances of energy monitoring machines to create the model navigate to digital twins the models pane appears from the models pane, click the create a model tile the create a model dialog box appears click the type drop down list and select asset enter the name of the model in the name field (for example, energy monitoring model ) (optional) enter a short description of the model in the description field click add the new model appears in the models pane after creating the model, you can docid\ seuz jpdj0jootaa4nktn with the following parameters model static attributes the static attributes will need to be customized for each instance asset line model manufacturer location plant transformations the transformations are based on the sample payload above energyratedescription { "value" "$energyratedescription", "timestamp" "$timestamp" } energyrate { "value" "$energyrate", "timestamp" "$timestamp" } energyused { "value" "$energyused", "timestamp" "$timestamp" } shift { "value" "$shift", "timestamp" "$timestamp" } starthour { "value" "$starthour", "timestamp" "$timestamp" } season { "value" "$season", "timestamp" "$timestamp" } cost { "value" "$cost", "timestamp" "$timestamp" } the list of transformations would display as the following model dynamic attributes the dynamic attributes will use the appropriate schemaid (transformation) to generate values name unit (optional) datatype (optional) schemaid (optional) cost usd cost energyratedescription energyratedescription energyrate usd/kwh energyrate energyused energyused shift shift starthour starthour season season power kw hierarchy the output for the model will be based on the hierarchy, which would categorize the dynamic and static attributes into telemetry or properties it would look like the following step 2 create instances once the model is configured, you will need to docid\ qptn23xppdeoxsnuygc o for each energy monitoring device at each site one of the instances is described below based on the topics for the data in the user scenario description instance static attributes you will customize the model static attributes to the specific instance attribute name attribute value asset machine 2 line line 1 model model 112233 manufacturer siemens location canada plant toronto instance dynamic attributes you will configure the appropriate topics in the user scenario description to the dynamic attributes configured in the model name unit datatype topic schemaid (optional) power kw devicehub alias p2 electrical panel l3 machine2 cost usd flowtodt emd l3 machine2 cost energyratedescription flowtodt emd l3 machine2 energyratedescription energyrate usd/kwh flowtodt emd l3 machine2 energyrate energyused flowtodt emd l3 machine2 energyused shift flowtodt emd l3 machine2 shift starthour flowtodt emd l3 machine2 starthour season flowtodt emd l3 machine2 season